Remaining Useful Life Prediction via a Data-Driven Deep Learning Fusion Model-CALAP
Author:
Affiliation:
1. School of Computer Science, Yangtze University, Jinzhou, China
2. School of Mechanical Engineering, Yangtze University, Jinzhou, China
3. School of Electronic Information, Yangtze University, Jinzhou, China
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hubei Province of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10273993.pdf?arnumber=10273993
Reference61 articles.
1. Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning
2. Deep discriminative transfer learning network for cross-machine fault diagnosis
3. A Predictive Maintenance Method for Shearer Key Parts Based on Qualitative and Quantitative Analysis of Monitoring Data
4. Relationship Transfer Domain Generalization Network for Rotating Machinery Fault Diagnosis Under Different Working Conditions
5. A Fast Learning Algorithm for Deep Belief Nets
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